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- Light-addressable potentiometric sensor (3)
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- hydrogen peroxide (3)
- impedance spectroscopy (3)
- Bacillus atrophaeus (2)
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A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals.
In this work, a cell-based biosensor to evaluate the sterilization efficacy of hydrogen peroxide vapor sterilization processes is characterized. The transducer of the biosensor is based on interdigitated gold electrodes fabricated on an inert glass substrate. Impedance spectroscopy is applied to evaluate the sensor behavior and the alteration of test microorganisms due to the sterilization process. These alterations are related to changes in relative permittivity and electrical conductivity of the bacterial spores. Sensor measurements are conducted with and without bacterial spores (Bacillus atrophaeus), as well as after an industrial sterilization protocol. Equivalent two-dimensional numerical models based on finite element method of the periodic finger structures of the interdigitated gold electrodes are designed and validated using COMSOL® Multiphysics software by the application of known dielectric properties. The validated models are used to compute the electrical properties at different sensor states (blank, loaded with spores, and after sterilization). As a final result, we will derive and tabulate the frequency-dependent electrical parameters of the spore layer using a novel model that combines experimental data with numerical optimization techniques.
Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.
For pelvic floor disorders that cannot be treated with non-surgical procedures, minimally invasive surgery has become a more frequent and safer repair procedure. More than 20 million prosthetic meshes are implanted each year worldwide. The simple selection of a single synthetic mesh construction for any level and type of pelvic floor dysfunctions without adopting the design to specific requirements increase the risks for mesh related complications. Adverse events are closely related to chronic foreign body reaction, with enhanced formation of scar tissue around the surgical meshes, manifested as pain, mesh erosion in adjacent structures (with organ tissue cut), mesh shrinkage, mesh rejection and eventually recurrence. Such events, especially scar formation depend on effective porosity of the mesh, which decreases discontinuously at a critical stretch when pore areas decrease making the surgical reconstruction ineffective that further augments the re-operation costs. The extent of fibrotic reaction is increased with higher amount of foreign body material, larger surface, small pore size or with inadequate textile elasticity. Standardized studies of different meshes are essential to evaluate influencing factors for the failure and success of the reconstruction. Measurements of elasticity and tensile strength have to consider the mesh anisotropy as result of the textile structure. An appropriate mesh then should show some integration with limited scar reaction and preserved pores that are filled with local fat tissue. This chapter reviews various tissue reactions to different monofilament mesh implants that are used for incontinence and hernia repairs and study their mechanical behavior. This helps to predict the functional and biological outcomes after tissue reinforcement with meshes and permits further optimization of the meshes for the specific indications to improve the success of the surgical treatment.
An amperometric bi-enzyme biosensor based on substrate recycling principle for the amplification of the sensor signal has been developed for the detection of adrenaline in blood. Adrenaline can be used as biomarker verifying successful adrenal venous sampling procedure. The adrenaline biosensor has been realized via modification of a galvanic oxygen sensor with a bi-enzyme membrane combining a genetically modified laccase and a pyrroloquinoline quinone-dependent glucose dehydrogenase. The measurement conditions such as pH value and temperature were optimized to enhance the sensor performance. A high sensitivity and a low detection limit of about 0.5–1 nM adrenaline have been achieved in phosphate buffer at pH 7.4, relevant for measurements in blood samples. The sensitivity of the biosensor to other catecholamines such as noradrenaline, dopamine and dobutamine has been studied. Finally, the sensor has been successfully applied for the detection of adrenaline in human blood plasma.
A field-effect biosensor employing tobacco mosaic virus (TMV) particles as scaffolds for enzyme immobilization is presented. Nanotubular TMV scaffolds allow a dense immobilization of precisely positioned enzymes with retained activity. To demonstrate feasibility of this new strategy, a penicillin sensor has been developed by coupling a penicillinase with virus particles as a model system. The developed field-effect penicillin biosensor consists of an Al-p-Si-SiO₂-Ta₂O₅-TMV structure and has been electrochemically characterized in buffer solutions containing different concentrations of penicillin G. In addition, the morphology of the biosensor surface with virus particles was characterized by scanning electron microscopy and atomic force microscopy methods. The sensors possessed a high penicillin sensitivity of ~ 92 mV/dec in a nearly-linear range from 0.1 mM to 10 mM, and a low detection limit of about 50 µM. The long-term stability of the penicillin biosensor was periodically tested over a time period of about one year without any significant loss of sensitivity. The biosensor has also been successfully applied for penicillin detection in bovine milk samples.
Magnetic detection structure for Lab-on-Chip applications based on the frequency mixing technique
(2018)
A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding.
Prosthetic textile implants of different shapes, sizes and polymers are used to correct the apical prolapse after hysterectomy (removal of the uterus). The selection of the implant before or during minimally invasive surgery depends on the patient’s anatomical defect, intended function after reconstruction and most importantly the surgeon’s preference. Weakness or damage of the supporting tissues during childbirth, menopause or previous pelvic surgeries may put females in higher risk of prolapse. Numerical simulations of reconstructed pelvic floor with weakened tissues and organ supported by textile product models: DynaMesh®-PRS soft, DynaMesh®-PRP soft and DynaMesh®-CESA from FEG Textiletechnik mbH, Germany are compared.
The porosity of surgical meshes makes them flexible for large elastic deformation and establishes the healing conditions of good tissue in growth. The biomechanic modeling of orthotropic and compressible materials requires new materials models and simulstaneoaus fit of deformation in the load direction as well as trannsversely to to load. This nonlinear modeling can be achieved by an optical deformation measurement. At the same time the full field deformation measurement allows the dermination of the change of porosity with deformation. Also the socalled effective porosity, which has been defined to asses the tisssue interatcion with the mesh implants, can be determined from the global deformation of the surgical meshes.
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
Heating efficiency of magnetic nanoparticles decreases with gradual immobilization in hydrogels
(2019)
Monitoring the cellular metabolism of bacteria in (bio)fermentation processes is crucial to control and steer them, and to prevent undesired disturbances linked to metabolically inactive microorganisms. In this context, cell-based biosensors can play an important role to improve the quality and increase the yield of such processes. This work describes the simultaneous analysis of the metabolic behavior of three different types of bacteria by means of a differential light-addressable potentiometric sensor (LAPS) set-up. The study includes Lactobacillus brevis, Corynebacterium glutamicum, and Escherichia coli, which are often applied in fermentation processes in bioreactors. Differential measurements were carried out to compensate undesirable influences such as sensor signal drift, and pH value variation during the measurements. Furthermore, calibration curves of the cellular metabolism were established as a function of the glucose concentration or cell number variation with all three model microorganisms. In this context, simultaneous (bio)sensing with the multi-organism LAPS-based set-up can open new possibilities for a cost-effective, rapid detection of the extracellular acidification of bacteria on a single sensor chip. It can be applied to evaluate the metabolic response of bacteria populations in a (bio)fermentation process, for instance, in the biogas fermentation process.
Enzyme-catalyzed reactions have been designed to mimic various Boolean logic gates in the general framework of unconventional biomolecular computing. While some of the logic gates, particularly OR, AND, are easy to realize with biocatalytic reactions and have been reported in numerous publications, some other, like NXOR, are very challenging and have not been realized yet with enzyme reactions. The paper reports on a novel approach to mimicking the NXOR logic gate using the bell-shaped enzyme activity dependent on pH values. Shifting pH from the optimum value to the acidic or basic values by using acid or base inputs (meaning 1,0 and 0,1 inputs) inhibits the enzyme reaction, while keeping the optimum pH (assuming 0,0 and 1,1 input combinations) preserves a high enzyme activity. The challenging part of the present approach is the selection of an enzyme with a well-demonstrated bell-shape activity dependence on the pH value. While many enzymes can satisfy this condition, we selected pyrroloquinoline quinone (PQQ)-dependent glucose dehydrogenase as this enzyme has the optimum pH center-located on the pH scale allowing the enzyme activity change by the acidic and basic pH shift from the optimum value corresponding to the highest activity. The present NXOR gate is added to the biomolecular “toolbox” as a new example of Boolean logic gates based on enzyme reactions.
Hydrogen peroxide (H2O2) is a typical surface sterilization agent for packaging materials used in the pharmaceutical, food and beverage industries. We use the finite-elements method to analyze the conceptual design of an in-line thermal evaporation unit to produce a heated gas mixture of air and evaporated H2O2 solution. For the numerical model, the required phase-transition variables of pure H2O2 solution and of the aerosol mixture are acquired from vapor-liquid equilibrium (VLE) diagrams derived from vapor-pressure formulations. This work combines homogeneous single-phase turbulent flow with heat-transfer physics to describe the operation of the evaporation unit. We introduce the apparent heat-capacity concept to approximate the non-isothermal phase-transition process of the H2O2-containing aerosol. Empirical and analytical functions are defined to represent the temperature- and pressure-dependent material properties of the aqueous H2O2 solution, the aerosol and the gas mixture. To validate the numerical model, the simulation results are compared to experimental data on the heating power required to produce the gas mixture. This shows good agreement with the deviations below 10%. Experimental observations on the formation of deposits due to the evaporation of stabilized H2O2 solution fits the prediction made from simulation results.
Production and Characterization of Porous Fibroin Scaffolds for Regenerative Medical Application
(2019)
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
The MYOTONES experiment is the first to monitor changes in the basic biomechanical properties (tone, elasticity and stiffness) of the resting human myofascial system due to microgravity with a oninvasive, portable device on board the ISS. The MyotonPRO device applies several brief mechanical stimuli to the surface of the skin, and the natural oscillation signals of the tissue beneath are detected and computed by the MyotonPRO. Thus, an objective, quick and easy determination of the state of the underlying tissue is possible.
Two preflight, four inflight and four post flight measurements were performed on a male astronaut using the same 10 measurement points (MP) for each session. MPs were located on the plantar fascia, Achilles tendon, M. soleus, M. gastrocnemius, M. multifidus, M. splenius capitis, M. deltoideus anterior, M. rectus femoris, infrapatellar tendon, M. tibialis anterior. Subcutaneous tissues thickness above the MPs was measured using ultrasound imaging. Magnetic resonance images (MRI) of lower limb muscles and functional tests were also performed pre- and postflight.
Our first measurements on board the ISS confirmed increased tone and stiffness of the lumbar multifidus muscle, an important trunk stabilizer, dysfunction of which is known to be associated with back pain. Furthermore, reduced tone and stiffness of Achilles tendon and plantar fascia were observed inflight vs. preflight, confirming previous findings from terrestrial analog studies and parabolic
flights. Unexpectedly, the deltoid showed negative inflight changes in tone and stiffness, and increased elasticity, suggesting a potential risk of muscle atrophy in longer spaceflight that should be addressed by adequate inflight countermeasure protocols. Most values from limb and back MPS showed deflected patterns (in either directions) from inflight shortly after the re-entry phase on the landing day and one week later. Most parameter values then normalized to baseline after 3 weeks likely due to 1G re-adaptation and possible outcome of the reconditioning protocol. No major changes in subcutaneous tissues thickness above the MPs were found inflight vs preflight, suggesting no bias (i.e., fluid shift, extreme tissue thickening or loss). Pre- and postflight MRI and functional tests showed negligible changes in calf muscle size, power and force, which is likely due to training effects from current inflight exercise protocols.
The MYOTONES experiment is currently ongoing to collect data from further crew members. The potential impact of this research is to better understand the effects of microgravity and countermeasures over the time course of an ISS mission cycle. This will enable exercise countermeasures to be tailored
Training-induced increase in Achilles tendon stiffness affects tendon strain pattern during running
(2019)
Background
During the stance phase of running, the elasticity of the Achilles tendon enables the utilisation of elastic energy and allows beneficial contractile conditions for the triceps surae muscles. However, the effect of changes in tendon mechanical properties induced by chronic loading is still poorly understood. We tested the hypothesis that a training-induced increase in Achilles tendon stiffness would result in reduced tendon strain during the stance phase of running, which would reduce fascicle strains in the triceps surae muscles, particularly in the mono-articular soleus.
Methods
Eleven subjects were assigned to a training group performing isometric singleleg plantarflexion contractions three times per week for ten weeks, and another ten subjects formed a control group. Before and after the training period, Achilles tendon stiffness was estimated, and muscle-tendon mechanics were assessed during running at preferred speed using ultrasonography, kinematics and kinetics.
Results
Achilles tendon stiffness increased by 18% (P <0:01) in the training group, but the associated reduction in strain seen during isometric contractions was not statistically significant. Tendon elongation during the stance phase of running was similar after training, but tendon recoil was reduced by 30% (P <0:01), while estimated tendon force remained unchanged. Neither gastrocnemius medialis nor soleus fascicle shortening during stance was affected by training.
Discussion
These results show that a training-induced increase in Achilles tendon
stiffness altered tendon behaviour during running. Despite training-induced changes in tendon mechanical properties and recoil behaviour, the data suggest that fascicle shortening patterns were preserved for the running speed that we examined. The asymmetrical changes in tendon strain patterns supports the notion that simple inseries models do not fully explain the mechanical output of the muscle-tendon unit during a complex task like running.